We are looking for an Area Lead Analytics Engineer to shape the technical direction of analytics engineering across our Revenue, Purchase, and Orders domains.
The Revenue, Purchase & Orders area sits at the heart of some of the most critical customer journeys and commercial systems in Vinted’s Marketplace business unit. Its scope spans Revenue, including pricing and advertising; Purchase, including checkout and transaction flows; and the Orders lifecycle, from a successful purchase through order management and completion.
Together, these domains form a broad and highly interconnected data landscape. As Area Lead Analytics Engineer, you will help ensure that the underlying data foundations evolve coherently and at scale. You will work across domains to identify shared concepts and dependencies, address structural data and architectural challenges, and guide the area toward a more scalable, consistent, and sustainable data ecosystem.
This is a senior Individual Contributor role combining hands-on engineering with architectural leadership. You will partner closely with area and domain leads, define technical standards and reusable patterns, build scalable data products, and reduce systemic complexity as our data ecosystem grows.
Your impact will extend beyond the area itself. You will help raise engineering quality and consistency across the wider Data Science & Analytics (DSA) function, working closely with Analytics Engineers, Data Scientists, Decision Scientists, Engineering, Product, and Business teams.
- Set the long-term technical direction across Revenue, Purchase, and Orders.
- Design and build scalable, reliable, and cost-efficient data products.
- Identify cross-domain dependencies and ensure shared concepts are consistently represented in data models and architecture.
- Define standards for data modeling, semantic layers, event data, observability, reliability, and testing.
- Lead technical decisions for cross-domain initiatives and create reusable patterns and architectural guardrails.
- Drive improvements in data quality, maintainability, ownership, cost efficiency, and operational excellence across DSA.
- Partner with Engineering on event-driven and behavioral data, from event definitions and instrumentation to reliable downstream models.
- Mentor other ICs through technical guidance, design reviews, and code reviews.
